Environmental, Social and Governance (ESG) data management is the unsung hero of ESG compliance. While ESG principles, missions and goals emphasize an organization’s vision to do better — it’s the meticulous collection, analysis and interpretation of data that can truly allow companies to turn ideas into tangible actions and informative outcomes. In other words, ESG compliance starts with good data management.

What Is ESG Data Management?

Much like regular data management, ESG data management is the collection, storage and analysis of data — except this data is all related to ESG.

It’s an important aspect in today’s business landscape as it’s a connection between environmental, social and governance activities and impact, and corporate strategy and performance.

What is included in ESG data?

ESG data encompasses a wide range of information, both qualitative and quantitative, that assesses a company’s impact in three areas; it can include:

Environmental

• Carbon dioxide emissions
• Other greenhouse gases (GHG) and pollutants
• Water use
• Raw materials use
• Waste management
• Energy use and efficiency
• Pollution incidents

Social

• Workforce diversity
• Fair pay
• Workforce wellbeing
• Social responsibility in supply chain and consumption
• Community engagement
• Health and safety
• Human rights

Governance

• Board composition
• Executive compensation
• Data privacy and security
• Environmental and social controls
• Audit compliance
• Ethical decision-making practices
• Political contributions
• Customer and supplier checks

ESG data management vs. ESG governance

So, how does this all relate to the more well-known term ESG governance? You can think of it like this: ESG data management is a fish in the ESG governance pond. That’s because ESG data governance is a more holistic concept. It focuses on the framework, policies and practices that guide an organization’s ESG initiatives using the data provided by ESG data management to form the foundation of their framework.

ESG governance ensures that ESG programs have effective inputs, outputs, controls and transparency, including data management.

Why do you need to collect ESG data?

Besides informing ESG governance strategy, ESG data collection is essential for many reasons:

• Helps ESG risk management. ESG data helps identify and mitigate ESG risks. For example, understanding how much carbon emissions come from a company helps assess its climate impact and informs companies where to focus their attention to avoid violations against climate legislation.
• Attracts investors. In today’s business landscape, investors are making investment decisions with ESG performance data. The collection and reporting of ESG data allows organizations to meet these expectations and access a wider pool of investors.
• Reporting compliance. There are an increasing number of ESG disclosure requirements from governments and regulatory bodies. For example, the U.S. Securities and Exchange Commission (SEC) proposed rule changes that would require companies to include certain climate-related emissions disclosures. Similarly, the EU and governments around the globe are proposing (or have already implemented) ESG and ESG-related reporting legislation. For example, the Corporate Sustainability Reporting Directive (CSRD) in the EU. Effective ESG data collection helps companies with ESG reporting and ESG impact reductions as well as reduces the risk of penalties.
• Gives a competitive advantage. Organizations who collect ESG data and then use that data to strategize can gain a long-term competitive advantage as they’re able to discover new opportunities aligned with sustainability goals — such as attracting more investors, customers and employees. Being visibly progressive with environmental and societal improvements increases customer interest.
• Supports innovation. ESG data can uncover opportunities to innovate and improve operations. For example, reducing waste not only lowers its environmental impact, but also reduces waste costs.

There are plenty more advantages to collecting, managing and reporting ESG data. The key takeaway is that the benefits go far beyond compliance. They help organizations’ operations become more strategically aligned and successful in an increasingly ESG-conscious environment.

How Do I Capture ESG Data?

There are several ways you can capture ESG data, and your strategy will likely be informed by the type of data you’re looking to collect. However, one thing is clear: the digitization of ESG data collection is imperative. This includes the use of intelligent automation (IA) and robotic process automation (RPA). But before we delve further, it’s important to first understand the challenges of ESG data collection.

The challenges in collecting ESG data

Due to its nature, it can be complex and challenging to collect ESG data. Here are three primary challenges facing ESG data collection:

Data diversity

ESG data covers a broad range of information and ESG metrics, some spread across siloed systems within an organization and outside of it. Different departments, industries and organizations can also face unique ESG issues, making it impossible to create a one-size-fits-all approach for data collection.

Reliable data quality

Right now, ESG relies heavily on self-reporting, which can be prone to inaccuracies. Without a way to reliably collect accurate data, organizations may struggle to ensure the validity of the data. Another layer of difficulty is added here when you think about capturing qualitative data.

Data accuracy

Accessing data can be hard, especially for organizations who don’t have the necessary resources or tools to start. This challenge is also amplified when companies are operating in regions with limited reporting infrastructure for ESG, or when organizations are looking to access relevant data from suppliers, partners and subsidiaries.

Technology: Automate ESG Data Collection

Just as organizations use automation software to perform financial data collection and reporting, the same can be done for ESG data.

Intelligent automation (IA) is a combination of technologies that automate and optimize business processes, such as ESG data collection and pre-processing. IA includes robotic process automation (RPA), which is the use of digital workers to automate activities previously done by a human worker, such as data acquisition and data entry. Learn more about ESG Automation. 

Artificial intelligence (AI) is another component of IA that plays a role in ESG data collection – extracting data from unstructured sources and identifying patterns in data that indicate potential risks before humans would otherwise become aware.

IA is helping organizations minimize challenges by:

• Making data collection and processing more efficient.
• Reducing the risk of errors associated with manual data entry.
• Managing highly repetitive data acquisition, at scale and without errors.
• Accommodating scalability as data collection processes can remain effective even as an organization expands.
• Integrating with different data sources, including internal and external systems to have a holistic view of your ESG data.
• Providing decision-makers with real-time, accurate ESG information to make informed choices and respond to quickly emerging ESG issues.

These tools are more than just theory. For example, InvoiceBotz by WonderBotz and GLYNT are revolutionizing the way organizations capture, process, and report on ESG data. InvoiceBotz, invoice processing automation software, uses SS&C Blue Prism intelligent automation and AI to gather and process invoice data, down to line-item level. GLYNT is helping to make sustainability data as rigorously prepared as financial data. Both solutions are boosting data accuracy and consistency and enhancing transparency in sustainability and ESG reporting.

What data is required for ESG reporting?

ESG reporting is already a legal requirement in some countries, and other regions are close behind. As ESG regulations evolve, there will be changes to the reporting required (hence the data that needs to be collected to support the reports). Using IA for data collection allows changes to be made with ease.

Some organizations are already publishing their ESG data by adding ESG sections to their annual reports and corporate governance strategies. At the same time, data aggregators are already creating metrics around ESG and publishing ESG ratings and ESG scores.

Master Evolving ESG Data

As ESG reporting requirements continue to evolve, so do the demands on ESG data collection. It can feel like a never-ending performance, requiring skill, agility and an unwavering focus to keep every new requirement and demand aloft — almost overwhelming.

But with help from intelligent automation and other digital solutions, you can master ESG data management and prevent yourself from sinking under all the regulations, frameworks and guidelines that come your way.